Reliability of regional climate model simulations of extremes and of long-term climate

Natural Hazards and Earth System Science

Volumn 4, Issue 3, 2004, Pages 417-431

  Bohm U ^a,b   Kucken M ^a   Hauffe, D ^a   Gerstengarbe, E W ^a   Werner, P C ^a   Flechsig, M ^a   Keuler, K ^c   Block, A ^c   Ahrens, W ^c   Nocke, Th ^d  

^a POTSDAM INSTITUTE FOR CLIMATE IMPACT RESEARCH   (Germany)

^b UNIVERSITY OF POTSDAM   (Germany)

^c BRANDENBURG UNIVERSITY OF TECHNOLOGY   (Germany)

^d UNIVERSITY OF ROSTOCK   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATE MODELING; REGIONAL CLIMATE; RELIABILITY ANALYSIS;

EID: 4544294986     PISSN: 15618633     EISSN: None     Source Type: Journal    
DOI: 10.5194/nhess-4-417-2004     Document Type: Article

References (30)

1. Böhm, U.: Eine Methode zur Validierung von Klimamodellen für die Klimawirkungsforschung hinsichtlich der Wiedergabe extremer Ereignisse, PhD thesis, Freie Universität Berlin, Department of Earth Sciences, 33-40, 1999.
2. Böhm, U., Hauffe, D., and Kücken, M.: The New Local Model (LM) of the Deutscher Wetterdienst, Part III: User Guide - The preparation of ECMWF re-analyses and the interpolation program era21m for nested long-term model simulations. Potsdam-Institut für Klimafolgenforschung, Department Climate System, 2002.
3. Böhm, U., Gerstengarbe, F.-W., Hauffe, D., Kücken, M., Österle, H., and Werner, P.C.: Dynamic Regional Climate Modeling and Sensitivity Experiments for the Northeast of Brazil, in: Global Change and Regional Impacts, edited by Gaiser, T., Krol, M., Frischkorn, H., and de Araújo, J. C.: G. Springer, Berlin, Heidelberg, New York, 153-170, 2003.
4. Christensen, J. H., Machenhauer, B., Jones, R. G., Schär, C., Ruti, P. M., Castro, M., and Visconti, G.: Validation of present-day regional climate simulations over Europe, LAM simulations with observed boundary conditions, Clim. Dynam., Vol. 13, No. 7-8, 489-506, 1997.
5. Dickinson, R.: Modeling Evapotranspiration for Three-dimensional Global Models, in: Climate Processes and Climate Sensitivity. Geophysical Monograph 29, Maurice Ewing Vol. 5, American Geophysical Union, Washington, D.C., 58-72, 1984.
6. Doms, G. and Schättler, U.: The Nonhydrostatic Limited-Area Model LM (Local Model) of DWD, Part I: Scientific Documentation, Deutscher Wetterdienst, Business Unit Research and Development, 1999.
7. Flechsig, M., Böhm, U., Nocke, T., and Rachimow, C.: The Multi-Run Simulation Environment SimEnv., User's Guide for Version V1.03, www.pik-potsdam.de/topik/pikuliar/simenv/home/, 2003.
8. Forgy, E. W.: Cluster Analysis of multivariate data: efficiency versus interpretability of classifications. Biometrics 21, 768-769, 1965.
9. Frei, C., Christensen, J. H., Déqué, M., Jacob, D., Jones, R. G., and Vidale, P. L.: Daily Precipitation Statistics in Regional Climate Models: Evaluation and Intercomparison for the European Alps, J. Geo. Res.-A., Vol. 108, No. D3, 4127-4130, 2003.
10. Gerstengarbe, F.-W. and Werner, P. C.: A method for the statistical definition of extreme-value regions and their application to meteorological time series, Z. Meteorol., 39, (4), 224-226, 1989.
11. Gerstengarbe, F.-W. and Werner, P. C.: A Method to Estimate the Statistical Confidence of Cluster Separation, Theor. App. C., Vol. 57, No. 1-2, 103-110, 1997.
12. Gerstengarbe, F.-W., Werner, P. C., Fraedrich, K.: Applying non-hierarchical cluster analysis algorithms to climate classification: some problems and their solution, Theor. App. C., Vol. 61, 143-150, 1999.
13. Gibson, J. K., Kallberg, P., Uppala, S., Hernandez, A., Nomura, A., and Serrano, E.: ECMWF re-analysis project report series, 1. ERA description, European Centre for Medium-range Weather Forecasts (ECMWF), Reading, UK, 1997.
14. Havre, S., Hetzler, E., Whitney, P., and Nowell, L.: Theme River: Visualizing thematic changes in large document collections, ACM T. Graph., Vol. 8, No. 1, 9-20, 2002.
15. IPCC: Climate Change 2001: Contribution of Working Group I to the third Assessment Report of the IPCC, Cambridge University Press, 583-638, 2001.
16. Jacob, D., Claussen, M., Majewski, D., Podzun, R., and Rockel, B.: REMO - a model for climate research and weather forecast, Research activities in Atmospheric and Oceanic Modelling, WMO/JCSU/IOC Report, 1995.
17. Jones, R. G., Murphy, J. M., and Noguer, M.: Simulation of Climate Change over Europe using a nested regional climate model, I: Assessment of control climate, including sensitivity to location of lateral boundaries, Q. J. R. Meteo., Vol. 121, 1413-1449, 1995.
18. Kücken, M., Gerstengarbe, F.-W. and Werner, P. C.: Cluster analysis results of regional climate model simulations in the PIDCAP period, Boreal Env. Res., Vol. 7, No 3, 219-223, 2002.
19. Kücken, M. and Hauffe, D.: The Nonhydrostatic Limited Area Model LM (Local Model) of DWD with PIK extensions, Part III: Extensions User Guide, Potsdam-Institut für Klimafolgenforschung, 2002.
20. Machenhauer, B., Windelband, M., Botzet, M., Jones, R. G., and Déqué, M.: Validation of present-day regional climate simulations over Europe: Nested LAM and Variable Resolution Global Model Simulations wit Observed or Mixed Layer Ocean Boundary Conditions, Report No. 191, Max-Planck-Institut für Meteorologie, Hamburg, 9-23, 1996.
21. Machenhauer, B., Windelband, M., Botzet, M., Christensen, J. H., Déqué, M., Jones, R. G., Ruti, P. M., and Visconti, G.: Validation and Analysis of Regional Present-Day Climate and Climate Change Simulations over Europe, Report No. 275, Max-Planck-Institut für Meteorologie, 26-54, 1998.
22. New, M., Hulme, M., and Jones, P.: Representing twentieth-century space-time climate variability, part II, Development of 1901-96 monthly grids of terrestrial surface climate, J. Climate, Vol. 13, 2217-2238, 2000.
23. Nocke, T., Böhm, U., Schumann, H., and Flechsig, M.: Information Visualization Supporting Modeling and Evaluation Tasks For Climate Models, in: Proceedings of the 2003 Winter Simulation Conference, December 7-10, New Orleans, edited by Chick, S., Sanchez, P. J. S., Ferin, D., and Morrice, D.J., 2003.
24. Pettitt, A. N.: A Non-parametric Approach to the Change-Point Problem. Applied Statistics 28, No.2, 126-135, 1979.
25. Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T.: Numerical Recipes, The Art of Scientific Computing, Cambridge University Press, Chapter 13, 1986.
26. Roeckner, E., Arpe, K., Bentsson, L., Christoph, M., Claussen, M., Dümenil, L., Esch, M., Giorgetta, M., Schleese, U., and Schulzweida, U.: The atmospheric general circulation model ECHAM-4, Max-Planck-Institut für Meteorology, Report No. 218, 1996.
27. Steinhausen, D. und Langer, K.: Clusteranalyse: Eine Einführung in Methoden und Verfahren der automatischen Klassifikation, Walter-deGruyter-Verlag, 100-138, 1977.
28. Takle, E. S., Gutowski Jr., W. J., Arritt, R. W., Pan, Z., Anderson, C. J., Silva, R., Caya, D., Chen, S.-C., Christensen, J. H., Hong, S.-Y., Juang, H.-M. H., Katzfey, J. J., Lapenta, W. M., Laprise, R., Lopez, P., McGregor, J., and Roads, J. O.: Project to Intercompare Regional Climate Simulations (PIRCS): Description and initial results, J. Geo. Res.-A., Vol. 104, No. D16, 19 443-19 462, 1999.
29. Taubenheim, J.: Statistische Auswertung geophysikalischer und meteorologischer Daten, Akademische Verlagsgesellschaft Geest & Porting, Leipzig, 1969.
30. Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geo. Res.-A., Vol. 106, No. D7, 7183-7192, 2001.